BUPT-GAMMA / Uncovering-the-Structural-Fairness-in-Graph-Contrastive-Learning
Source code for NeurIPS 2022 paper "Uncovering the Structural Fairness in Graph Contrastive Learning"
☆29Updated 2 years ago
Alternatives and similar repositories for Uncovering-the-Structural-Fairness-in-Graph-Contrastive-Learning
Users that are interested in Uncovering-the-Structural-Fairness-in-Graph-Contrastive-Learning are comparing it to the libraries listed below
Sorting:
- [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating☆51Updated 2 years ago
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆30Updated last year
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆43Updated 2 years ago
- GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)☆31Updated 11 months ago
- ☆37Updated 3 years ago
- A collection of papers on Graph Structural Learning (GSL)☆54Updated last year
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆45Updated last year
- Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning☆49Updated last year
- ☆22Updated 7 months ago
- Ratioanle-aware Graph Contrastive Learning codebase☆43Updated last year
- Official Code: TheWebConf 2022 Compact Graph Structure Learning via Mutual Information Compression☆24Updated last year
- Code for NeurIPS 2022 paper "Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discriminat…☆55Updated 2 years ago
- The repository of "Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark" (KDD'24)☆11Updated 6 months ago
- An official PyTorch implementation of "Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels" (WSDM 2022))☆32Updated 2 years ago
- "GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification" in KDD'23☆30Updated last year
- ☆26Updated 2 years ago
- Source code for WWW 2021 paper "Graph Structure Estimation Neural Networks"☆58Updated 3 years ago
- [KDD'23] Learning Strong Graph Neural Networks with Weak Information☆43Updated last year
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆81Updated 5 months ago
- [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection☆40Updated 2 years ago
- The source code of SpCo☆35Updated last year
- [NeurIPS 2023] "Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift" by Yongduo Sui, Qitian Wu, Jiancan Wu, Q…☆17Updated last year
- The Open Source Code For ICML 2023 Paper "Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-pron…☆15Updated last year
- This is the official repository for NeurIPS 2023 paper "Curriculum Learning for Graph Neural Networks: Which Edges Should We Learn First"☆15Updated last year
- ☆18Updated 2 years ago
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆22Updated last year
- Pytorch implementation of EvenNet.☆20Updated 2 years ago
- Code for AAAI-2024 paper: Graph Contrastive Invariant Learning from the Causal Perspective☆24Updated last year
- NIPS 24: Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights☆43Updated 4 months ago
- [WSDM 2023] "Alleviating Structrual Distribution Shift in Graph Anomaly Detection" by Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, H…☆21Updated last year